基于新型分数阶粒子群优化算法的分布式电源选址定容

Distributed Generation’s Location and Capacity Optimization Using a Novel Fractional Particle Swarm Algorithm

大规模分布式电源并网带来巨大的经济效益和环境效益的同时也会对电网的稳定性造成威胁。为使配电网可以消纳更高比例的分布式电源,需要对分布式电源接入电网的位置及容量进行优化。首先,建立了风速、光照强度、负荷的不确定性分析模型,构建了以年综合费用最低为目标函数的分布式电源选址定容规划模型;然后,提出新型分数阶粒子群优化算法,测试了算法在复杂优化问题上的性能。最后,IEEE-33节点配电网算例的仿真结果验证了所建立模型的合理性与所提算法的有效性。

Large-scale distributed generation grid connection brings huge economic and environmental benefits,but also threatens the stability of the grid.To undertake a higher penetration of distributed generation,it is necessary to optimize the location and capacity of the distributed generation connected to the grid.Firstly,the uncertainty analysis model of wind speed,light intensity,and load is established.Then,a planning model with the lowest annual comprehensive cost as the objective function is constructed.Secondly,a novel fractional particle swarm optimization algorithm is proposed,and the performance of the algorithm on complex optimization problems is tested.Finally,the simulation results of the IEEE-33 distribution network example verify the rationality of the established model and the effectiveness of the proposed algorithm.